Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	20,466
2	New Jersey	19,535
3	Rhode Island	15,870
4	Massachusetts	15,797
5	District of Columbia	14,632
6	Connecticut	13,046
7	Louisiana	12,520
8	Delaware	11,783
9	Illinois	11,415
10	Maryland	11,272
11	Arizona	10,908
12	Nebraska	9,922
13	Iowa	9,239
14	Mississippi	9,155
15	Alabama	7,759
16	South Dakota	7,645
17	Virginia	7,355
18	Georgia	7,278
19	Pennsylvania	7,125
20	Florida	7,096
21	Michigan	7,094
22	South Carolina	7,069
23	Utah	6,975
24	Indiana	6,942
25	Arkansas	6,884
26	Minnesota	6,443
27	Tennessee	6,269
28	North Carolina	6,203
29	Nevada	6,032
30	California	5,875
31	New Mexico	5,793
32	Texas	5,749
33	Colorado	5,677
34	Wisconsin	5,448
35	Kansas	5,021
36	North Dakota	4,704
37	Washington	4,535
38	Ohio	4,430
39	New Hampshire	4,252
40	Missouri	3,629
41	Kentucky	3,562
42	Oklahoma	3,476
43	Idaho	3,426
44	Wyoming	2,569
45	Maine	2,420
46	Puerto Rico	2,337
47	Oregon	2,053
48	Vermont	1,935
49	West Virginia	1,620
50	Alaska	1,547
51	Montana	904
52	Hawaii	636

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Arizona	423
2	Florida	308
3	South Carolina	288
4	Louisiana	238
5	Nevada	236
6	Texas	207
7	Alabama	201
8	Georgia	195
9	Mississippi	192
10	California	174
11	Utah	169
12	Arkansas	162
13	Idaho	150
14	Tennessee	146
15	North Carolina	138
16	Delaware	131
17	Iowa	100
18	Kansas	98
19	Oklahoma	93
20	Wisconsin	84
21	New Mexico	83
22	Minnesota	75
23	Missouri	74
24	Nebraska	72
25	Ohio	66
26	Washington	66
27	Maryland	61
28	Virginia	60
29	Illinois	55
30	Wyoming	54
31	District of Columbia	52
32	Indiana	51
33	North Dakota	51
34	South Dakota	51
35	Alaska	47
36	Pennsylvania	47
37	Rhode Island	47
38	Oregon	44
39	Kentucky	43
40	Puerto Rico	41
41	Colorado	40
42	Montana	35
43	Michigan	34
44	New Jersey	29
45	Connecticut	28
46	New York	25
47	Maine	24
48	West Virginia	22
49	Massachusetts	21
50	New Hampshire	15
51	Hawaii	10
52	Vermont	4

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	1,692
2	New York	1,633
3	Connecticut	1,212
4	Massachusetts	1,168
5	Rhode Island	896
6	District of Columbia	780
7	Louisiana	692
8	Michigan	620
9	Illinois	563
10	Maryland	527
11	Delaware	522
12	Pennsylvania	522
13	Indiana	392
14	Mississippi	360
15	Colorado	293
16	New Hampshire	272
17	Minnesota	261
18	Georgia	259
19	Ohio	244
20	New Mexico	237
21	Iowa	227
22	Arizona	226
23	Virginia	206
24	Alabama	193
25	Washington	175
26	Missouri	168
27	Nevada	164
28	Florida	163
29	California	153
30	Nebraska	144
31	South Carolina	143
32	Wisconsin	136
33	Kentucky	131
34	North Carolina	129
35	North Dakota	115
36	South Dakota	102
37	Oklahoma	97
38	Kansas	94
39	Arkansas	89
40	Vermont	89
41	Tennessee	87
42	Texas	85
43	Maine	78
44	Utah	53
45	Idaho	51
46	West Virginia	51
47	Oregon	49
48	Puerto Rico	47
49	Wyoming	34
50	Montana	20
51	Alaska	16
52	Hawaii	12

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New York	11
2	Rhode Island	7
3	Mississippi	4
4	New Jersey	3
5	Alabama	2
6	Arizona	2
7	Louisiana	2
8	Arkansas	1
9	California	1
10	Connecticut	1
11	District of Columbia	1
12	Florida	1
13	Illinois	1
14	Indiana	1
15	Iowa	1
16	Maryland	1
17	Michigan	1
18	Minnesota	1
19	Nebraska	1
20	Ohio	1
21	Pennsylvania	1
22	South Carolina	1
23	Virginia	1
24	Alaska	0
25	Colorado	0
26	Delaware	0
27	Georgia	0
28	Hawaii	0
29	Idaho	0
30	Kansas	0
31	Kentucky	0
32	Maine	0
33	Massachusetts	0
34	Missouri	0
35	Montana	0
36	Nevada	0
37	New Hampshire	0
38	New Mexico	0
39	North Carolina	0
40	North Dakota	0
41	Oklahoma	0
42	Oregon	0
43	Puerto Rico	0
44	South Dakota	0
45	Tennessee	0
46	Texas	0
47	Utah	0
48	Vermont	0
49	Washington	0
50	West Virginia	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	131,602	1	99
Lake	Tennessee	98,347	2	99
Dakota	Nebraska	88,934	3	99
Buena Vista	Iowa	86,391	4	99
Lincoln	Arkansas	79,699	5	99
Davidson	Tennessee	14,125	203	93
Richland	South Carolina	8,462	490	84
Orange	California	4,359	1042	66
York	South Carolina	4,285	1058	66
Pierce	Washington	3,190	1362	56

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	3,784	1	99
Randolph	Georgia	3,688	2	99
Terrell	Georgia	3,165	3	99
Early	Georgia	3,042	4	99
Emporia city	Virginia	2,619	5	99
Richland	South Carolina	200	676	78
Davidson	Tennessee	163	771	75
Pierce	Washington	112	988	68
Orange	California	107	1011	67
York	South Carolina	43	1532	51

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.